> Imo the right advice is to either store things in some sort of offset format
Yeah, I agree that's what it comes down to, basically. It's more or less what I meant by "keep things near 1". I almost said "keep things near 0", but I didn't want to suggest that 1e-12 is somehow better than 1e+12. Really, it's more like "try to keep '1 float unit' to be about the size of the stuff you care about in your calculation".
> E.g., say you're adding some velocity to an objects position
As I interpret this example, I think it would be beneficial to re-center things to a common nearby origin, rather than doing them in some far-away-from-0 space. The more calculations being done (each one introducing some error), the more it matters.
For the specific case of "add X to each number" maybe it wouldn't matter, but I'm talking about arbitrary sequences of math being done.
If each of your calculations (applying velocity, maybe some rotation, etc) introduces some floating point roundoff error, then that is a potentially large accumulated absolute value when far away from the origin (eg: could be off-by-kilometers rather than off-by-meters). But if you normalize things down to small relative numbers first, produce all your error in that space, then transform back to faraway-space, that's only one opportunity to produce big-size error, rather than several accumulated. In other words, you've taken your local off-by-meters value, transformed it into global kilometer-size space, and so maybe your final result is off-by-1-kilometer, due to some rounding or whatnot. Whereas if you did all your computation in kilometer-space, then each step of math you do can introduce additional off-by-kilometer error, and you could be off-by-10s-of-kilometers in the end.
This whole conversation has got me doubting myself, so I made an example in godbolt that hopefully is clear: https://godbolt.org/z/MfP7e7Tbh
Yeah, I agree that's what it comes down to, basically. It's more or less what I meant by "keep things near 1". I almost said "keep things near 0", but I didn't want to suggest that 1e-12 is somehow better than 1e+12. Really, it's more like "try to keep '1 float unit' to be about the size of the stuff you care about in your calculation".
> E.g., say you're adding some velocity to an objects position
As I interpret this example, I think it would be beneficial to re-center things to a common nearby origin, rather than doing them in some far-away-from-0 space. The more calculations being done (each one introducing some error), the more it matters.
For the specific case of "add X to each number" maybe it wouldn't matter, but I'm talking about arbitrary sequences of math being done.
If each of your calculations (applying velocity, maybe some rotation, etc) introduces some floating point roundoff error, then that is a potentially large accumulated absolute value when far away from the origin (eg: could be off-by-kilometers rather than off-by-meters). But if you normalize things down to small relative numbers first, produce all your error in that space, then transform back to faraway-space, that's only one opportunity to produce big-size error, rather than several accumulated. In other words, you've taken your local off-by-meters value, transformed it into global kilometer-size space, and so maybe your final result is off-by-1-kilometer, due to some rounding or whatnot. Whereas if you did all your computation in kilometer-space, then each step of math you do can introduce additional off-by-kilometer error, and you could be off-by-10s-of-kilometers in the end.
This whole conversation has got me doubting myself, so I made an example in godbolt that hopefully is clear: https://godbolt.org/z/MfP7e7Tbh